Open AccessCardiometabolic risk factors in predicting obstructive coronary artery disease in patients with non-ST-segment elevation acute coronary syndrome
Author(s) -
Б. И. Гельцер,
M. M. Tsivanyuk,
K. I. Shakhgeldyan,
Е. Д. Емцева,
A. A. Vishnevskiy
Publication year - 2021
Publication title -
rossijskij kardiologičeskij žurnal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.141
H-Index - 14
eISSN - 2618-7620
pISSN - 1560-4071
DOI - 10.15829/1560-4071-2021-4494
Subject(s) - medicine , acute coronary syndrome , cardiology , coronary artery disease , logistic regression , confidence interval , univariate analysis , receiver operating characteristic , area under the curve , prospective cohort study , myocardial infarction , multivariate analysis
Aim . To develop predictive models of obstructive coronary artery disease (OPCA) in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) based on the predictive potential of cardiometabolic risk (CMR) factors. Material and methods . This prospective observational cohort study included 495 patients with NSTE-ACS (median age, 62 years; 95% confidence interval [60; 64]), who underwent invasive coronary angiography (CAG). Two groups of persons were identified, the first of which consisted of 345 (69,6%) patients with OPCA (stenosis ≥50%), and the second — 150 (30,4%) without OPCA ( 3,5 mmol/L, waist-to-hip ratio ≥0,9, waist-to-height ratio ≥0,69, atherogenic index ≥3,4, lipid accumulation product index ≥38,5 cm*mmol/L, uric acid ≥356 pmol/L) and 2 continuous (high density lipoprotein cholesterol and insulin resistance index) variables. Conclusion . The developed algorithm for selecting predictors made it possible to determine their significant predictive threshold values and weighting coefficients characterizing the degree of influence on endpoints. The ensemble of MLR models demonstrated the highest accuracy of OPCA prediction before the CAG. The predictive accuracy of the SVM and RF models was significantly lower.